Build an Autonomous AI-Run Office (n8n + LLM + Causal Brain)
Budget: ₹37,500 – ₹75,000 INR
We’re developing a self-operating digital office that functions like a real company — departments, coordination, reasoning, publishing, and cost management — all automated through n8n workflows integrated with AI models and a causal reasoning engine (“the Brain”).
This system will act as a complete back-office and front-office framework where each department (Technology, Operations, Marketing, Finance, Research, and Support) has its own workflow “employee.”
The environment must allow manual, test, and auto modes, approvals, error recovery, and human oversight via a central Control Center.
Core Objectives
Deploy n8n (cloud or VPS) and configure staging / production environments.
Design modular workflows representing departments (data, research, content, finance, support, reliability).
Build a Control Center to start, pause, or test individual departments, view health, and manage approvals.
Integrate LLMs for content generation, insight writing, and reasoning.
Connect a Causal Brain module that runs “what-if” or cause-effect simulations and feeds results into insights.
Implement cost tracking, retries, and daily guardrails.
Provide documentation, exports, and a short Loom walkthrough.
Deliverables
n8n setup and configuration (with environment variables).
Departmental workflows with standard event schema (scan.completed, insight.drafted, etc.).
Control Center interface for mode toggles and monitoring.
Integration of the Brain simulation API.
Complete documentation and exports.
Next Step
Please share:
A short outline of your proposed architecture and tools.
Estimated timeline and prior n8n / AI workflow experience.
A sample export or Loom demo (if available).
Short-listed candidates will receive the detailed architecture brief describing departments, event coordination, payload design, and simulation logic before finalizing scope and cost.
This system will act as a complete back-office and front-office framework where each department (Technology, Operations, Marketing, Finance, Research, and Support) has its own workflow “employee.”
The environment must allow manual, test, and auto modes, approvals, error recovery, and human oversight via a central Control Center.
Core Objectives
Deploy n8n (cloud or VPS) and configure staging / production environments.
Design modular workflows representing departments (data, research, content, finance, support, reliability).
Build a Control Center to start, pause, or test individual departments, view health, and manage approvals.
Integrate LLMs for content generation, insight writing, and reasoning.
Connect a Causal Brain module that runs “what-if” or cause-effect simulations and feeds results into insights.
Implement cost tracking, retries, and daily guardrails.
Provide documentation, exports, and a short Loom walkthrough.
Deliverables
n8n setup and configuration (with environment variables).
Departmental workflows with standard event schema (scan.completed, insight.drafted, etc.).
Control Center interface for mode toggles and monitoring.
Integration of the Brain simulation API.
Complete documentation and exports.
Next Step
Please share:
A short outline of your proposed architecture and tools.
Estimated timeline and prior n8n / AI workflow experience.
A sample export or Loom demo (if available).
Short-listed candidates will receive the detailed architecture brief describing departments, event coordination, payload design, and simulation logic before finalizing scope and cost.